29 August 2016 Gait recognition system based on (2D)2 PCA and HMM
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Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 1003310 (2016) https://doi.org/10.1117/12.2244848
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
Abstract
In order to carry on the gait recognition fast and effectively, a novel gait recognition based on (2D)2 PCA and HMM is proposed in this paper . Firstly, establish a stable background model by using the adaptive background modeling and get the goal of human motion by using background subtraction. As for the existence of the shadow of the human body and inanity, this article makes shadow detection and elimination by using color space conversion respectively and handles human target image soothingly by using regional filling and morphological filtering on smoothing. the number of high-dimensional video images is high, uses the (2D)2PCA features extracted to reduce the dimensions so as to solve the curse of dimensionality, makes use of HMM to classification training of Gait features extracted, then the classification results are analyzed. This gait recognition system is achieved loading OpenCV under VC++6.0 visual library. Our experimental results demonstrate that the method is effective and has achieved a good recognition effect on CASIA gait database including three different multi-views.
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Jianqiang Huang, Zhengming Yi, Xiaoying Wang, Huan Wu, "Gait recognition system based on (2D)2 PCA and HMM", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003310 (29 August 2016); doi: 10.1117/12.2244848; https://doi.org/10.1117/12.2244848
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